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Glossary


F-test


A statistical test of significance in which the difference between two variances is tested. A variance is the square of a standard deviation. The F-test is often used to compare the imprecision of two analytical methods. The hypothesis being tested (called a null hypothesis) is that there is no difference between the two variances. If the calculated F-value is greater than the critical value which is obtained from a statistics table, then the null hypothesis is rejected. This means that a difference exists and that the difference is statistically significant, or real. If the calculated F-value is less than the critical value, the null hypothesis cannot be rejected, therefore, there is no difference between the two variances being tested, and the difference is not statistically significant.


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